“We build models to increase productivity, under the justified assumption that it's cheaper to manipulate the model than the real thing. Models then enable cheaper exploration and reasoning about some universe of discourse. One important application of models is to understand a real, abstract, or hypothetical problem domain that a computer system will reflect. This is done by abstraction, classification, and generalization of subject-matter entities into an appropriate set of classes and their behavior.”

Source: MDA Distilled. Principles of Model-Driven Architecture, 2003, p. 35-36.

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Stephen J. Mellor13

British computer scientist 1952

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“If we are to use effectively these abstract models and this descriptive material, we must have a comparable exploration of the criteria for determining what abstract model it is best to use for particular kinds of problems, what entities in the abstract model are to be identified with what observable entities, and what features of the problem or of the circumstances have the greatest effect on the accuracy of the predictions yielded by a particular model or theory.”

Milton Friedman (1912–2006) American economist, statistician, and writer

"The Methodology of Positive Economics" (1953)

“Since it can be argued that both science and engineering are concerned with the study of real systems and their behavior, it follows that a general theory should be concerned with the study of general systems… It suffices for the present discussion to consider a general system as an abstract analogue or model of a class of real systems. General systems theory is then a theory of general models.”

Mihajlo D. Mesarovic (1928) Serbian academic

Mesarovic (1964) cited in: Shatrughna P. Sinha (1991) Instant encyclopaedia of geography. 1. Introduction to geography. Mittal Publications, p. 467

“In object-oriented analysis, we seek to model the world by identifying the classes and objects that form the vocabulary of the problem domain, and in object-oriented design, we invent the abstractions and mechanisms that provide the behavior that this model requires.”

Grady Booch (1955) American software engineer

Source: Object-oriented design: With Applications, (1991), p. 141

“The analysis model will not be a reflection of what the problem domain looks like… The reason is simply to get a more maintainable structure where changes will be local and thus manageable. We thus do not model reality as it is, as object orientation is often said to do, but we model the reality as we want to see it and to highlight what is important in our application.”

Ivar Jacobson (1939) Swedish computer scientist

Source: Object-Oriented Software Engineering: A Use Case Driven Approach (1992), p. 185: cited in: " Object Oriented Software Engineering: A Use Case Driven Approach Ivar Jacobson, et al. (1992) http://tedfelix.com/software/jacobson1992.html", Book review by Ted Felix on tedfelix.com, 2006.

“Simulation is the use of models and/or the actual conditions of either the thing being modeled or the environment in which it operates, with the models or conditions in physical, mathematical, or some other form. The purpose of simulation is to explore the various results which might be obtained from the real system by subjecting the model to representative environments which are equivalent to, or in some way representative of, the situations it is desired to understand or investigate. Simulation may involve system hardware and the actual physical environment, or it may involve mathematical models subjected to mathematical forcing or disturbance functions representative of the systems conditions to be studied.”

Harold Chestnut (1917–2001) American engineer

Source: Systems Engineering Tools, (1965), p. 111 as cited in

“The growing complexity of software is the motivation behind work on industrializing software development. In particular, current research in the area of model driven engineering (MDE) is primarily concerned with reducing the gap between problem and software implementation domains through the use of technologies that support systematic transformation of problem-level abstractions to software implementations. The complexity of bridging the gap is tackled through the use of models that describe complex systems at multiple levels of abstraction and from a variety of perspectives, and through automated support for transforming and analyzing models. In the MDE vision of software development, models are the primary artifacts of development and developers rely on computer-based technologies to transform models to running systems.”

Bernhard Rumpe (1967) German computer scientist

Source: Model-driven development of complex software: A research roadmap (2007), p. 37

“To an outsider, the most significant innovation in the global warming controversy is the overt reliance that is being placed on models. Back in the days of nuclear winter, computer models were invoked to add weight to a conclusion: “These results are derived with the help of a computer model.” But now, large-scale computer models are seen as generating data in themselves. No longer are models judged by how well they reproduce data from the real world—increasingly, models provide the data. As if they were themselves a reality. And indeed they are, when we are projecting forward.”

Michael Crichton (1942–2008) American author, screenwriter, film producer

Aliens Cause Global Warming (2003)

“I hate flowers — I paint them because they're cheaper than models and they don't move!”

Georgia O'Keeffe (1887–1986) American artist

quote in Portrait of an Artist: A Biography of Georgia O'Keeffe, Laurie Lisle, Viking Press, New York, 1981, p. 180
1980s

“Knowledge management often generates theories that are too general or abstract to be easily testable. In some cases, simulation modeling can help. [WE have developed] an agent-based simulation model derived from a conceptual framework, the Information Space or I-Space and use it to explore the differences between a neoclassical and a Schumpeterian information environment.”

Max Boisot (1943–2011) British academic and educator

Boisot, M. H., Canals, A., & MacMillan, I. (2004). " Simulating I-Space (SIS): An agent-based approach to modeling knowledge flows http://entrepreneurship.wharton.upenn.edu/research/simispace3_200405.pdf." Working papers of the Sol C. Snider Entrepreneurial Research Center, Wharton School, University of Pennsylvania.

“Scientific models have all these connotations. They are representations of states, objects, and events. They are idealized in the sense that they are less complicated than reality and hence easier to use for research purposes. These models are easier to manipulate and "carry" than the real thing. The simplicity of models, compared with reality, lies in the fact that only the relevant properties of reality are represented.”

Russell L. Ackoff (1919–2009) Scientist

Source: 1960s, Scientific method: optimizing applied research decisions, 1962, p. 108 as cited in: Joe H. Ward, Earl Jennings (1973) Introduction to linear models. p. 4.

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Stephen J. Mellor13

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